Privacy preserving group linkage

Fengjun Li, Yuxin Chen, Bo Luo, Dongwon Lee, Peng Liu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

The problem of privacy preserving record linkage is to find the intersection of records from two parties, while not revealing any private records to each other. Recently, group linkage has been introduced to measure the similarity of groups of records [19]. When we extend the traditional privacy preserving record linkage methods to group linkage measurement, group membership privacy becomes vulnerable - record identity could be discovered from unlinked groups. In this paper, we introduce threshold privacy preserving group linkage (TPPGL) schemes, in which both parties only learn whether or not the groups are linked. Therefore, our approach is secure under group membership inference attacks. In experiments, we show that using the proposed TPPGL schemes, group membership privacy is well protected against inference attacks with a reasonable overhead.

Original languageEnglish (US)
Title of host publicationScientific and Statistical Database Management - 23rd International Conference, SSDBM 2011, Proceedings
Pages432-450
Number of pages19
DOIs
StatePublished - Aug 11 2011
Event23rd International Conference on Scientific and Statistical Database Management, SSDBM 2011 - Portland, OR, United States
Duration: Jul 20 2011Jul 22 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6809 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other23rd International Conference on Scientific and Statistical Database Management, SSDBM 2011
CountryUnited States
CityPortland, OR
Period7/20/117/22/11

Fingerprint

Privacy Preserving
Linkage
Experiments
Record Linkage
Privacy
Attack
Group Scheme
Intersection

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Li, F., Chen, Y., Luo, B., Lee, D., & Liu, P. (2011). Privacy preserving group linkage. In Scientific and Statistical Database Management - 23rd International Conference, SSDBM 2011, Proceedings (pp. 432-450). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6809 LNCS). https://doi.org/10.1007/978-3-642-22351-8_27
Li, Fengjun ; Chen, Yuxin ; Luo, Bo ; Lee, Dongwon ; Liu, Peng. / Privacy preserving group linkage. Scientific and Statistical Database Management - 23rd International Conference, SSDBM 2011, Proceedings. 2011. pp. 432-450 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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Li, F, Chen, Y, Luo, B, Lee, D & Liu, P 2011, Privacy preserving group linkage. in Scientific and Statistical Database Management - 23rd International Conference, SSDBM 2011, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 6809 LNCS, pp. 432-450, 23rd International Conference on Scientific and Statistical Database Management, SSDBM 2011, Portland, OR, United States, 7/20/11. https://doi.org/10.1007/978-3-642-22351-8_27

Privacy preserving group linkage. / Li, Fengjun; Chen, Yuxin; Luo, Bo; Lee, Dongwon; Liu, Peng.

Scientific and Statistical Database Management - 23rd International Conference, SSDBM 2011, Proceedings. 2011. p. 432-450 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6809 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Li F, Chen Y, Luo B, Lee D, Liu P. Privacy preserving group linkage. In Scientific and Statistical Database Management - 23rd International Conference, SSDBM 2011, Proceedings. 2011. p. 432-450. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-642-22351-8_27